Purpose

To explore the use of a multistate repeated, time-to-categorical event model describing the frequency, severity and duration of migraines.

Methods

Subject level data from patients in placebo arms from two efficacy trials for migraine-preventive treatments were used. Models were developed using NONMEM 7.3. A survival model was combined with an ordered categorical model to form the repeated-time-to-start of categorical migraine event model, which simultaneously described the time-to-start of migraines and the severity of the starting migraine event. This was linked to a repeated-time-to-end of migraine event model with different hazard functions depending on the severity of the ongoing migraine event. Model performance was internally and externally qualified.

Results

The successfully qualified model showed that patients responding to placebo had a reduction in migraine incidence rate, and a decreased proportion of severe migraines. There was an increase in moderate migraine duration, an increased proportion of mild migraines and a reduction in proportion of severe migraines. Age was related to migraine duration.

Conclusions

The model represents an innovative framework for clinical trial modeling and simulation, and successfully describes placebo effect in migraine prevention. This approach can be adapted to investigate exposure-response relationship of drugs and can also be implemented in other therapeutic areas where the rate, duration and severity of disease episodes are relevant to trial outcomes.

中文翻译：

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用于同时分析偏头痛事件的频率，持续时间和严重程度的创新药理学方法。

目的

探索使用描述偏头痛发生频率，严重程度和持续时间的多状态重复时间分类事件模型。

方法

使用来自两项偏头痛预防治疗功效试验的安慰剂组患者的受试者水平数据。使用NONMEM 7.3开发模型。将生存模型与有序分类模型组合在一起，以形成分类偏头痛事件模型的重复开始时间，该模型同时描述了偏头痛的开始时间和起始偏头痛事件的严重性。这与重复偏头痛事件模型的终止时间有关，该模型具有不同的危害功能，具体取决于进行中的偏头痛事件的严重程度。模型的性能在内部和外部都是合格的。

结果

成功合格的模型表明，对安慰剂有反应的患者偏头痛发生率降低，严重偏头痛的比例降低。中度偏头痛持续时间增加，轻度偏头痛比例增加，重度偏头痛比例降低。年龄与偏头痛持续时间有关。

结论

该模型代表了用于临床试验建模和模拟的创新框架，并成功描述了偏头痛预防中的安慰剂作用。这种方法可以适用于调查药物的暴露-反应关系，也可以在其他疾病发生率，持续时间和严重程度与试验结果相关的治疗领域中实施。